The rapidly evolving COVID-19 pandemic has created a need for timely data from the healthcare systems for research. To meet this need, several large new data consortia have been developed that require frequent updating and sharing of electronic health record (EHR) data in different common data models (CDMs) to create multi-institutional databases for research. Traditionally, each CDM has had a custom pipeline for extract, transform, and load operations for production and incremental updates of data feeds to the networks from raw EHR data. However, the demands of COVID-19 research for timely data are far higher, and the requirements for updating faster than previous collaborative research using national data networks have increased. New approaches need to be developed to address these demands.

中文翻译：

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从规范的快速医疗互操作性资源数据库中自动生成研究数据集市：应用于 COVID-19 研究

迅速发展的 COVID-19 大流行产生了对来自医疗保健系统的及时数据进行研究的需求。为了满足这一需求，已经开发了几个大型新数据联盟，需要频繁更新和共享不同通用数据模型 (CDM) 中的电子健康记录 (EHR) 数据，以创建多机构数据库进行研究。传统上，每个 CDM 都有一个自定义管道，用于提取、转换和加载操作，用于从原始 EHR 数据到网络的数据馈送的生产和增量更新。但是，COVID-19 研究对及时数据的要求要高得多，并且比以前使用国家数据网络的协作研究更新得更快的要求也增加了。需要开发新方法来满足这些需求。